Author: Maciej Fijalkowski <[email protected]> Branch: extradoc Changeset: r3785:b7f86c9c1884 Date: 2011-06-24 10:05 +0200 http://bitbucket.org/pypy/extradoc/changeset/b7f86c9c1884/
Log: merge diff --git a/sprintinfo/genova-pegli-2011/directions.txt b/sprintinfo/genova-pegli-2011/directions.txt new file mode 100644 --- /dev/null +++ b/sprintinfo/genova-pegli-2011/directions.txt @@ -0,0 +1,38 @@ +How to go to Genova Pegli +========================= + +By train +-------- + +- http://www.trenitalia.com + +- Take a long distance train to Genova Piazza Principe or Genova Brignole + (both works; in case of doubt, pick Genova Principe as it's slightly closer + to Pegli) + +- From there, take a regional train to Genova Pegli: take one whose final + destination is Genova Voltri, Savona or Ventimiglia. Beware that not all of + those actually stops in Pegli, so make sure that yours does :-) (in case of + doubt, you can ask a random person on the platform, they'll know it for + sure) + +- You can search for the timetable at the trenitalia.com website + +- This is the map from the Genova Pegli station to the Hotel: http://maps.google.it/maps?saddr=Genova+Pegli&daddr=Lungomare+di+Pegli,+22,+16155+Genova+(Albergo+Puppo)&hl=it&sll=44.42542,8.81594&sspn=0.001927,0.003793&geocode=FVrkpQId9oeGACllN1h7SD_TEjEhQe02_AQZnQ%3BFYDdpQIdaYGGACHNe85zd7hOuykraHuSRz_TEjHnjlgjZyCfOA&mra=ltm&dirflg=w&z=18 + + +By plane +-------- + +- http://www.airport.genova.it/v2/ + +- From the airport, take the "Volabus" until the stop "Via Cornigliano / + Stazione FS": + http://www.airport.genova.it/v2/index.php?option=com_content&view=article&id=67&Itemid=136&lang=en + +- From the Genova Cornigliano train station, take a regional train to Genova + Pegli whose final destination is Genova Voltri, Savona or Ventimiglia. You + can use the same ticket as for the Volabus + +- Look at the map above for the hotel + diff --git a/talk/iwtc11/paper.tex b/talk/iwtc11/paper.tex --- a/talk/iwtc11/paper.tex +++ b/talk/iwtc11/paper.tex @@ -808,8 +808,11 @@ jump($L_1$, $p_{0}$, $i_8$) \end{lstlisting} -XXX explain that this is effectively type-specializing a loop - +If all the optimizations presented above are applied, the resulting +optimized peeled loop will consist of a single integer addition +only. That is it will become type-specialized to the types of the +variables \lstinline{step} and \lstinline{y}, and the overhead of +using boxed values is removed. \section{Benchmarks} @@ -825,7 +828,6 @@ chose to present benchmarks of small numeric kernels where loop peeling can show its use. -XXX we either need to explain that we use C++ or consistently use C \begin{figure} \begin{center} {\smaller @@ -838,7 +840,7 @@ \hline conv3(1e6) & 77.15 & 9.58 & 1.69 & 0.77 & 0.74 \\ \hline -conv3x3(1000) & 23.72 & 12.77 & 0.07 & 0.05 & 0.25 \\ +conv3x3(1000) & 236.96 & 128.88 & 0.70 & 0.41 & 0.25 \\ \hline conv3x3(3) & 23.85 & 12.77 & 0.10 & 0.07 & 0.27 \\ \hline @@ -848,7 +850,7 @@ \hline dilate3x3(1000) & 23.29 & 12.99 & 0.41 & 0.39 & 0.26 \\ \hline -sobel(1000) & - & - & - & - & 0.20 \\ +sobel(1000) & 181.49 & 95.05 & 0.71 & 0.42 & 0.20 \\ \hline sqrt(Fix16) & 744.35 & 421.65 & 3.93 & 2.14 & 0.96 \\ \hline @@ -863,7 +865,11 @@ } \end{center} \label{fig:benchmarks} -\caption{Benchmark Results in Seconds} +\caption{Benchmark Results in Seconds. Arrays of length $10^5$ and + $10^6$ and matrixes of size $1000\times 1000$ and $1000000 \times + 3$ are used. The one used in each benchmark is indicated in + the leftmost column. For the matrixes, only the number of rows are + specified.} \end{figure} \subsection{Python} @@ -897,10 +903,12 @@ \end{itemize} The sobel and conv3x3 benchmarks are implemented -on top of a custom two-dimensional array class, Array2D. +on top of a custom two-dimensional array class. It is a simple straight forward implementation providing 2 dimensionall -indexing with out of bounds checks. +indexing with out of bounds checks. For the C implementations it is +implemented as a C++ class. The other benchmarks are implemented in +plain C. Benchmarks were run on Intel i7 M620 @2.67GHz with 4M cache and 8G of RAM in 32bit mode. _______________________________________________ pypy-commit mailing list [email protected] http://mail.python.org/mailman/listinfo/pypy-commit
